Elizabeth Berry-Kravis is professor of child neurology at Rush University Medical Center in Chicago.
Elizabeth Berry-Kravis
Professor
Rush University Medical Center
From this contributor
Analysis offers new hope for failed fragile X drug
Eye tracking shows that mavoglurant, a once-abandoned experimental drug for fragile X syndrome, enters the brain and boosts social interest, says Elizabeth Berry-Kravis.
Analysis offers new hope for failed fragile X drug
Questions for Elizabeth Berry-Kravis: Dodging mouse traps
A mouse model of fragile X syndrome lacks a key feature of the condition, prompting researchers to look for other ways to test treatments.
Questions for Elizabeth Berry-Kravis: Dodging mouse traps
Questions for Elizabeth Berry-Kravis: Measuring drug effects
Drugs designed to treat fragile X syndrome have yet to show substantial benefits in people. But rather than abandon them, child neurologist Elizabeth Berry-Kravis suggests a new way to measure their effectiveness.
Questions for Elizabeth Berry-Kravis: Measuring drug effects
Explore more from The Transmitter
Leucovorin saga, and more
Here is a roundup of autism-related news and research spotted around the web for the week of 15 June.
Leucovorin saga, and more
Here is a roundup of autism-related news and research spotted around the web for the week of 15 June.
Models at the speed of thought: How AI coding is reshaping theoretical neuroscience
Agentic coding makes it possible to specify a neuroscience model in hours instead of months. Six neuroscientists weigh in on what that tectonic change may bring to the field.
Models at the speed of thought: How AI coding is reshaping theoretical neuroscience
Agentic coding makes it possible to specify a neuroscience model in hours instead of months. Six neuroscientists weigh in on what that tectonic change may bring to the field.
Writing science that humans and machines can read
Large language models are now routinely used to search, summarize and synthesize the literature at scales impossible for any individual researcher—yet scientific publishing has not adapted to that reality.
Writing science that humans and machines can read
Large language models are now routinely used to search, summarize and synthesize the literature at scales impossible for any individual researcher—yet scientific publishing has not adapted to that reality.